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ERC-AG - ERC Advanced Grant

Objetivo

Fluid mechanics are fundamental to collective behaviour in nature and technology. Fluids pervade complex systems at every scale, ranging from fish schools and flocking birds to bacterial colonies and nanoparticles for drug delivery. Despite its importance, little is known about the role of fluid mechanics in such applications. Is schooling the result of vortex dynamics synthesised by individual fish wakes or the result of behavioural traits? Is fish schooling energetically favourable? How does blood affect the collective transport of nanoparticles in cancer therapy?

We seek to answer these questions through computational methods that resolve the interaction of fluids with multiple, deforming bodies across scales. Our methods rely on the innovative coupling of multi-scale particles with multi-resolution algorithms and grids. Uncertainty quantification techniques will link computations with experimental data. Learning and optimisation algorithms will investigate the optimality of collective behaviour and its relevance to technological applications.Novel, scalable software, engineered to facilitate its broad use, will be made available to the scientific and industrial community.Our group has built strong foundations in computational methods, fluid mechanics, biophysics, nanotechnology and their interfaces and this project gives us the opportunity to reach new frontiers.

Our goal is to provide unprecedented information about vortex dynamics of fish schooling, one of the most intriguing patterns in nature. Increased insight will open new horizons for mechanical understanding of collective behaviour, suggest new experiments and contribute to the rational design of industrial applications ranging from robots to wind farms. We will also shed light on mass transport in tumour induced vasculature to enhance the efficacy of drug delivery by nanoparticles, one of the most promising routes for cancer therapy.